Services Data Engineering · 10+ years · 30+ enterprise programs

Data Engineering Services:
From Raw Data to Operational Decisions.

Infarsight Data Engineering services build the intelligence foundation that connects operational data to real-time business decisions, across ERP, CRM, IoT and operational systems. We build data pipelines and platforms designed for operational action, not just reporting.

What is Enterprise Data Engineering?

Enterprise data engineering is the practice of designing, building and maintaining the data pipelines, platforms and governance systems that connect raw operational data to business decisions. It covers data ingestion, transformation, quality management, real-time streaming and the infrastructure that makes AI and analytics possible at scale.

Microsoft Fabric Partner Databricks Ecosystem AWS · Azure · GCP Condense — Strategic Investment Informatica
10+
Years of data engineering delivery
30+
Enterprise data programs delivered
60%
Faster pipeline build with Condense
Near-zero
Silent data failures with BAU monitoring
The problem

Enterprises Are Drowning in Data
Yet Starved of Operational Decisions.

Data Exists, But Isn't Usable

Siloed across ERP, CRM, IoT and BI systems with no unified layer. Teams can't trust what they're looking at. Decisions are made on contested data.

Insights Arrive Too Late

Reports take hours or days. By the time data reaches decision-makers, the operational window has closed, and the cost of inaction has already compounded.

Manual, Brittle Pipelines

One-off scripts, manual extracts and fragile integrations break under scale, costing time, trust and money. Data quality collapses within 6 months of go-live.

No Single Source of Truth

Finance, Operations and Technology each have a different version of the same number. Every team defines "customer" differently. Decisions are built on a flawed foundation.

"We're trying to do AI. But we haven't even engineered our data like a product."

, Chief Digital Officer, Ports (USA)

The Infarsight difference

We Don't Just Deliver Data Pipelines.
We Own the Data Quality With You.

Operational Context First

We understand Travel, Ports and Mobility deeply. Our engineers don't just build pipelines, they understand the operational decisions those pipelines need to serve.

End-to-End Ownership

We connect data engineering directly to the automation and agentic AI layers. Your pipelines don't end at a dashboard, they feed the decision systems that run your operations.

Condense Accelerator

Our strategic investment in Condense reduces time to production-grade pipelines by up to 60%, pre-built connectors, governed templates and observability tooling built in.

BAU Commitment

We embed engineers into your operations for long-term data quality ownership. Unlike project-based delivery, we stay accountable for the health of the data systems we build.

What decision-ready data means

The 4C Framework.

Most organisations have data. Very few have data that is current, clean, connected and contextual enough to drive operational decisions without human intervention.

C

Current

Available at the moment the decision needs to be made, not hours or days later.

C

Clean

Governed, validated and consistent across every system that touches it.

C

Connected

Unified across ERP, CRM, IoT and operational systems into one coherent layer.

C

Contextual

Enriched with the operational metadata needed to trigger the right action automatically.

Our 7 data engineering service tracks

Targeted tracks, not one-size-fits-all.

Each track is designed for a specific data problem. We deploy what your operation actually needs.

TRACK 01

Business as Usual (BAU)

Your pipelines need to run like clockwork, monitored, maintained and trusted every day.

SQL ServerOraclePythonT-SQL
What we do
  • Monitor and maintain ETL/ELT pipelines 24/7
  • Fix issues before they impact reporting
  • Ensure timely and trusted data delivery
  • Root cause analysis & post-incident documentation
Why it matters
  • No more 3AM calls about failed jobs
  • Analysts stop babysitting data feeds
  • Regain trust in your daily data
TRACK 02

Data Streaming

Real-time pipelines that ingest, enrich and trigger actions the moment an event occurs.

KafkaCondenseAzure Event HubsDatabricks
What we do
  • Design real-time streaming pipelines
  • Ingest, enrich and trigger actions instantly
  • Monitor for lags, drops and anomalies
  • Resilient by design, retry logic & dead-letter queues
Why it matters
  • Make decisions in minutes, not hours
  • Power real-time customer experiences
  • Automate responses without human delay
TRACK 03

Data Quality Assessment

Audit every byte from ingestion to insights, identify hidden risks and fix broken pipelines before they break operations.

dbtSQL Rule EnginesAzure Purview
What we do
  • Completeness & accuracy scoring
  • Anomaly detection on key datasets
  • Identify hidden risks & missed opportunities
  • Detailed report with actionable fixes
Why it matters
  • Monetize unused data assets
  • Fix broken pipelines and cut waste
  • Migrate with clarity, not chaos
TRACK 04

Data Capturing (IoT & Edge)

Edge-to-boardroom ingestion, capturing data from cameras, meters, IoT devices and machines into scalable pipelines.

Azure IoT EdgeCondenseZeliot
What we do
  • Capture data from cameras, meters, IoT, machines
  • Design scalable ingestion pipelines
  • Handle initial and incremental loads
  • Edge processing for low-latency field intelligence
Why it matters
  • No more missing data from field devices
  • Plug new devices into your data fabric
  • Make field data work for the boardroom
TRACK 05

Data Movement & Modernisation

Migrate legacy infrastructure to cloud-native architectures without disrupting live operations.

MS FabricDatabricksdbt CloudAirflow
What we do
  • Ingest from apps, sensors, cloud & on-prem
  • Unify formats, resolve conflicts, standardise schema
  • Migrate legacy to cloud-native lakehouse
  • Full data lineage & observability throughout
Why it matters
  • Build a clean, scalable system of record
  • Eliminate integration delays & migration chaos
  • Enable AI/BI and reduce infrastructure costs
TRACK 06

Analytics Enablement

Turning data into self-serve intelligence that empowers operational decisions, not just executive reports.

Power BIDatabricksCondenseLooker
What we do
  • Align KPIs with operational business goals
  • Build real-time, role-based dashboards
  • Enable self-serve, action-ready analytics
  • BI platform setup, governance & certified datasets
Why it matters
  • Teams aligned on one version of truth
  • Cut reporting delays & Excel workarounds
  • Data teams focus on insights, not ad hoc requests
TRACK 07

Master Data Management

Creating a single, trusted version of your most critical operational data, customers, assets, locations, products.

MS PurviewAzure Data FactoryDataverse
What we do
  • Build a single source of truth for core entities
  • Clean, de-duplicate & standardise master data
  • Sync MDM across ERP, CRM, DWH & BI tools
  • Data stewardship & governance model
Why it matters
  • Eliminate silos with a 360° entity view
  • Enable consistent, cross-team analytics
  • Power personalisation, AI & automation
Industry application

Data Engineering Services Purpose-Built for
Travel, Ports and Mobility Operations.

Travel & Hospitality

  • Unified booking data across OTA, GDS & direct channels
  • Real-time yield pipelines for dynamic pricing
  • Guest data MDM, single guest profile across PMS
  • Disruption event feeds for automated rebooking

Ports & Logistics

  • Vessel tracking & berth scheduling data integration
  • Container dwell time analytics from gate sensor + ERP
  • Customs clearance & documentation pipelines
  • Port throughput KPI dashboards with real-time feeds

Fleet & Mobility

  • Vehicle telematics ingestion at scale, IoT to lakehouse
  • Fleet health scoring for predictive maintenance
  • Driver & route data MDM across dispatch systems
  • EV charging event streams & utilisation analytics

Airlines

  • Flight ops data, OAG, ACARS, flight plan integration
  • Passenger journey stitching across PSS, DCS & loyalty
  • Crew data management & rostering analytics
  • Revenue management data for yield operations
Strategic Investment

Condense

Infarsight's strategic investment in Condense — a real-time streaming platform that reduces time to production-grade pipelines by up to 60%. Pre-built connectors for Travel, Hospitality and Mobility source systems. Governance, lineage and observability built in from day one.

Explore Condense →
60%
Reduction in pipeline setup time
10+
Enterprise programs running on Condense
Built-in
Governance, lineage & observability
Weeks
Time to production-grade pipelines
How we engage

The data engineering workflow.

From operational problem to production data system, in a repeatable, governed process.

01

Discover

Data audit, source mapping, pain sizing. 1–2 weeks.

02

Design

Architecture blueprint, pipeline design, governance framework. 2–3 weeks.

03

Build

Pipeline development, integration, data quality rules. 4–12 weeks.

04

Operate

Monitoring, incident management, performance tuning. Ongoing.

05

Optimise

Query optimisation, new source onboarding, quality improvement. Continuous.

Related capabilities
Integration Services Agentic AI Engineering Condense Platform Real-Time Data Platform

Ready to build your data foundation?

We begin with a Data Readiness Assessment, mapping your current landscape, identifying highest-value opportunities and designing the architecture.

Book a Data Readiness Assessment →